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  • fujiisoup · 2 ✖

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  • xarray tutorial at SciPy 2018? · 2 ✖

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365796393 https://github.com/pydata/xarray/issues/1882#issuecomment-365796393 https://api.github.com/repos/pydata/xarray/issues/1882 MDEyOklzc3VlQ29tbWVudDM2NTc5NjM5Mw== fujiisoup 6815844 2018-02-15T01:06:00Z 2018-02-15T01:06:00Z MEMBER

For my part, I am working in the nuclear fusion field, where we have many kinds of high-dimensional measurement data. The size of each measurement is not so huge, but we have huge kinds of data taken on different coordinates. xarray also fits such situation. (I am also happy to share my snippest but my data is not big and I am not sure this fits the tutorial concept.)

xarray certainly helps me a lot, but I don't hear any usages of xarray around me. It might be a historical reason (many are still using a comersial software such as IDE). I think there is a certain market also in my field.

 
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   xarray tutorial at SciPy 2018? 293913247
365793506 https://github.com/pydata/xarray/issues/1882#issuecomment-365793506 https://api.github.com/repos/pydata/xarray/issues/1882 MDEyOklzc3VlQ29tbWVudDM2NTc5MzUwNg== fujiisoup 6815844 2018-02-15T00:48:13Z 2018-02-15T01:01:32Z MEMBER

My colleague in astronomy said that his common data format has been a set of few images taken with long exposure time and he didn't need to take care of big data until recently. I am not sure it is generally true for astronomy field. However, one of the recent streams in astrophysics is definitely the combination of the statistics and the huge amount of measurements, such as thousands of images constantly taken by telescopes. I suspect xarray could play more role also in this field (I am also an outsider though...).

 
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   xarray tutorial at SciPy 2018? 293913247

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